Transparency in Algorithms
Awareness of data usage is crucial for addressing the challenges posed by machine learning in various sectors. The lack of regulation has led to significant issues, particularly in policing and healthcare, where flawed algorithms can have real-world consequences. Both speakers emphasize the urgent need for transparency and accountability in how these technologies are deployed, highlighting the risks of opaque systems that affect people's lives.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
SDS 449: Fairness in A.I. — with Ayodele Odubela
Related Questions
Can technology invade our privacy as discussed in the episode When Machine Learning meets privacy - Episode 3 with Charles Radclyffe, the clip Tech Ethics Evolution, the episode 1135: Sandra Matz | How Algorithms Read and Reveal the Real You, the clip Surveillance and Choice, as well as in Mindscape 278 | Kieran Healy on the Technology of Ranking People and the clip Data Collection Insights?
Why would Jordan Harbinger publish an episode of his podcast on the topic of data collection that discusses the negative practices of social media platforms but then explain that his AI bot literally collects data and provides him analytics and summaries of what people ask it? Does this not strike Jordan as contradictory?